Demand on a road segment (e.g., the number of vehicles on the road segment) is often fluid, fluctuating based upon, among other things, the time-of-day, traffic accidents, weather conditions, road construction, road closures, and/or local events (e.g., which may draw a large number of attendees to a venue). As demand approaches and/or exceeds capacity for the road, traffic congestion may be created along the road segment and/or drivers may experience delayed travel times along the road segment.
Route planners (e.g., route navigation software) are frequently configured to identify a temporally shortest route(s) between a starting location and an ending location and/or to estimate the travel time for a route. While route planners frequently attempt to forecast traffic congestion along various road segments and/or forecast expected travel times along respective road segments to accurately identify the temporally shortest route and/or to estimate the travel time for a route, such forecasting is often challenging due to the fluid nature of traffic congestion.